EconPapers    
Economics at your fingertips  
 

Interactive neutrosophic optimization technique for multiobjective programming problems: an application to pharmaceutical supply chain management

Firoz Ahmad ()
Additional contact information
Firoz Ahmad: Aligarh Muslim University

Annals of Operations Research, 2022, vol. 311, issue 2, No 2, 585 pages

Abstract: Abstract Multiobjective optimization problems have a significant role in modeling and optimizing the framework of different real-life issues. It may not always be possible to obtain a single solution that satisfies each objective efficiently; however, there is ample opportunity to get a compromise solution to multiobjective programming problems (MOPPs). Neutrosophic set (NS) is the extension of fuzzy and intuitionistic fuzzy sets. Thus, based on NS, this study presents neutrosophic optimization models for MOPP under the neutrosophic fuzzy environment. We have developed three models while keeping in mind the maximal satisfactory degree of decision-maker(s). The proposed models are then applied to various discussed numerical examples, and solution results are compared with other approaches. Also, the propounded models are implemented in the pharmaceutical supply chain planning problem. The sensitivity analysis of the obtained outcomes at different criteria has been performed. At last, the conclusion and future research scope have been depicted effectively.

Keywords: Intuitionistic fuzzy parameters; Neutrosophic optimization methods; Multiobjective programming problem; Pharmaceutical supply chain management (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s10479-021-03997-2 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:annopr:v:311:y:2022:i:2:d:10.1007_s10479-021-03997-2

Ordering information: This journal article can be ordered from
http://www.springer.com/journal/10479

DOI: 10.1007/s10479-021-03997-2

Access Statistics for this article

Annals of Operations Research is currently edited by Endre Boros

More articles in Annals of Operations Research from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().

 
Page updated 2025-03-20
Handle: RePEc:spr:annopr:v:311:y:2022:i:2:d:10.1007_s10479-021-03997-2